{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7d0d179d",
   "metadata": {},
   "source": [
    "# THE CODE IS IN MY GITHUB!!!\n",
    "Go and checkout my github if you want the to_candle file!\n",
    "## https://github.com/kecoma1/Trading_BOT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "dc133857",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import to_candle"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1c665d2",
   "metadata": {},
   "source": [
    "## Candle dataframe\n",
    "This dataframe is obtained through the from_tick_to_candle function. The dataframe contains the following columns:\n",
    "* **TIME-UTC**: UTC-TIME since epoch in seconds.\n",
    "* **OPEN**: Open price of that candle.\n",
    "* **CLOSE**: Close price of the candle.\n",
    "* **HIGH**: Highest price of the candle.\n",
    "* **LOW**: Lowest price of the candle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "794baf27",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TIME-UTC</th>\n",
       "      <th>OPEN</th>\n",
       "      <th>CLOSE</th>\n",
       "      <th>HIGH</th>\n",
       "      <th>LOW</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.633298e+09</td>\n",
       "      <td>1.15996</td>\n",
       "      <td>1.15977</td>\n",
       "      <td>1.15996</td>\n",
       "      <td>1.15973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.633299e+09</td>\n",
       "      <td>1.15977</td>\n",
       "      <td>1.15975</td>\n",
       "      <td>1.15986</td>\n",
       "      <td>1.15973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.633300e+09</td>\n",
       "      <td>1.15975</td>\n",
       "      <td>1.15968</td>\n",
       "      <td>1.15984</td>\n",
       "      <td>1.15970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.633301e+09</td>\n",
       "      <td>1.15968</td>\n",
       "      <td>1.15963</td>\n",
       "      <td>1.15971</td>\n",
       "      <td>1.15961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.633302e+09</td>\n",
       "      <td>1.15963</td>\n",
       "      <td>1.16049</td>\n",
       "      <td>1.16060</td>\n",
       "      <td>1.15947</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       TIME-UTC     OPEN    CLOSE     HIGH      LOW\n",
       "0  1.633298e+09  1.15996  1.15977  1.15996  1.15973\n",
       "1  1.633299e+09  1.15977  1.15975  1.15986  1.15973\n",
       "2  1.633300e+09  1.15975  1.15968  1.15984  1.15970\n",
       "3  1.633301e+09  1.15968  1.15963  1.15971  1.15961\n",
       "4  1.633302e+09  1.15963  1.16049  1.16060  1.15947"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "candle_df = to_candle.from_tick_to_candle(\"EURUSD.csv\", 15*60)\n",
    "candle_df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ea75aa13",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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TWgQrbWCQMDoSZaZhN3Vbt7Qr67Q4OauqjDItHWk1YwqFEVLy2pa/Y9c0LmqwUhBx8d9ZkkveuYS7592NURhZXLKYq2s8bLFYWWXd0oUlCsWR4/999f/Y0bSjX9uclDGJO467o9syB4dqbmpq4pvf/Ga7Mh6PB6/Xy5gxY7pt6+STT8YYd+jwer1MmjTp0AzvBb0ZAnoOOKub/Cbgx8AjneQ9AXwgpZwEzAC2x9M/Ao6RUk4HdgF39dbg4UatpzIhAEkZab2uZykqAuCEen1oxojEJiXnGr/iqrKfY2s5ieI0PfrgvOzZyLjLqDYyHyEFSUFY7S7huJYIKxq/wQlefXP5kuYS/rLxbzy//XnSMHHus3Z++ozAYm3snwtWKI5CWkM1t/785je/6VDm4FDQH374ITNnzqSoqIjly5cn0j/99NNEO0899VSHdvqTHnsAUsplQoiibvLrgDohxLkHpgshUoAFwDXxcmH0N36klEsOKLoS+FZfDR8u1PpqyA7oMUCcWek9lG7DMqYIgNmNHiCZiBAEwmbslghGITmmZgQ/vuSX/OA/F7Jw0/uJeELGceOhbB/OAPjsMP+rJGatW4HITKPg2giVZjMbarajCS9XV/gAI+aIQDO6CEbC2MwWAN4re48le5fwrQnfaudtpFAMJD29qQ8mKSkpJCcns2fPHsaMGcOZZ57JmWeeyXnnnZfYE/hIM5CTwGOBeuBZIcR6IcRTQojkTspdB7zfVSNCiBuFEGuEEGvq6+sHytYhS62vhny/Pjafmp3RQ+k2zPn5CJOBvCb9i3VNuY89b2QTbNY1/1nLw+z/y3V8uquE+V+GCLn09KRpMwD4Rp2NYwNBHHX6sFOg0cLibXXc1NxCUDYR1sKctinYdr6oxqbassTn/139CJ/s+4S/bfjXYVy9QvH14q677uKWW27B5XIBeq8gGAx2X2kAGchJYBP6vMCtUspVQogngDuBX7cWEELcDUSBF7pqREr5V+CvAHPmzJEDaO+QpC7UzMSAftmm1N7PAQijEXN+NhGPj3/tCZNSLvBL8NVa8ddZMSfHOK9gFZ79Vhq36sHkYkKQMX0GfuDWhioyrD4+8ozAMn484ZISAvvtTNAXG3OMW8Ow3U7rHyTbDZtryziuYBL1/nr2BnWx3tmgYgopFK3ccsst+P1+5s2bh9VqxeFwcOKJJzJr1qyeKw8AAykAlUCllHJV/PNidAEAQAhxNfrk8qmy1SF9GBPTYqypXUOKJYXJmW27/9RGPGS3GNCEAVN6Wp/atBQVEd5YyTRqWOGZSBoe6jalgCbAABMurKbB07a2wH7DTVhz9ThChrBGpZZJrs+F48Rz8BsN1G/cyWR7EfeX72BGo0Y4koTpv24n+vgj5DZLfr/lDp7d9ATfm6nvUzouFKXM3HT4N0ehGOJ4ve0XYl5zzTVcc801gL4OoBUhBLfffju339556PXy8vJ2nxctWsSiRYv60dL2DNgQkJSyBqgQQkyMJ50KbAMQQpwF3AF8U0rpHygbjia+2P8FNyy5gUvfvTQRuiESi9AkI6Q3G3Fn5CIslj61aR03mYjXhNSgyRsPGa3FJ6E02PV6Pu4SO1GbnaLXFjP2pz/GmK7PM7jKkqhcnYk5GsZSVETBk38l7dvfxruynMmf2ghucUDhKIouOh+Ab1aHuKLFQ4uhij9vepwkTePkgA9NeIjEOo+JrlAoBpceBUAI8SKwApgohKgUQlwvhLhZCHFzPD9PCFEJ/BT4VbxM62vlrcALQohNwEzgoXj6nwAn8JEQYoMQ4i/9e1lHH+UNWxPHO5t2AlAXqEMCziZBML+gz21aiouRmiDiNxLwtolHyjnnYJ9zrF7GFyVp3DjsU6cihMDg1IUiUG8ldY/+VmMZMwZzbg55999H7i91hy2DppE6exam7GyEycBJdSHubGrm2y36gpa7GpspiERBSPa2VPf9higUigGnN15Al/eQXwN0+nSSUm4A5nSSPq6X9g0bqkr+nTj+av9Wjss/js31mzFoEqdbIziqqM9ttrqCrsz5CVMMn7alF49lxO/+H/VPPEHj357Ckt22xaQwGDBmZmJIspN93/24//EP7MdMTeRlXHUVwR07aXn9dewzZyCEIGnKGFp27iJtnI9rlsW41B1k7KIgq7PNAGyrq2BcxqhDuCsKhWIgUaEgBpEKTwWVnkoAqqJ+xofDWKNmttTryyVWV37O6GYNoyaxFY/tc/utAjA1sxDRUAfxxSXW4mKEyYQjPrYozOZ29Yo/eJ/iDz4g9cT5FD75FwzJ7Z23HCcvAiFImqNre/bP7iAWMrLrw3y81Tak10TlFxnkBvVopCWNlX22XaFQDDxKAAaRc14/h7NfPxuA/VqQkZEo2WErpe7dAHy1fzkn1ujj5/nHTOyyna4wZmZicDioe/hhkBLHggUAWMfpHTD7rFnk3HlHYlgnUc/pTISW7gznaadR/NESrOPH6+3MO4n8u3+GOW8EBX/6E4UP/BfBFjOmVbrXUrlLCYBCMRRRsYCGADd9dBMlMS9zozE0LcaXwXKag82Uhxq4ukl/EI+cXNzndoUQJM+fj2fJEpLmzWPEww/j/WwplmK9LWEwkBn3VOhru5aC9qN+aVfeQNqVN8Q/nUpmWQtNzzzD1FrBNpOKJKpQDEVUD2AIsLxKXwaeGYsxPewnRoRPy/S1cdHmTDSTGVNWVndNdMnIxx6l8KmnGPn4YxgdyaSee2675egDReb11yHMBq5ZGaQusqVXm9IoFEcrB4eDBmhpaeGqq66iuLiY4uJirrrqKlpa9P+Diy66iDfffDNRduLEiTzwwAOJz5dccgmvv/76gNutBOAAolqUD/Z8QEyLDfi5pJSYhN4Bm5c3D4Dp9VFOXOcFKXlv91sAmN02DLl5CMOh/amEyYTjGye220j+SGDKzMQxdyqjygSCGA9/9QRquYdiOHH99dczduxYSktLKS0tZcyYMdxwg95Lnj9/fiL+T2NjIw6HgxUrViTqrlixgvnz5w+4jUoADuD9Pe/z82U/5/ntzw/4uXwRH1EZ5WfH/oynTn+SL/ZVkbEhBeMGO+P3w6rmbdg1DbtPw1YwcsDtGQicZ1+ICBo4dWcmb5W9yrq6o3coKBAN8PetfycYHbxl+4qjh927d7N27Vp+/etE4APuuece1qxZQ2lpKSeeeGJCAJYvX855551HfX09Ukr27NmD3W4nLy9vwO1UcwAH4Aq5AFha8RlXT716QM/VulF7qjUVvHWkRKOU1CSRTJAztkBJAeRHY6QH/FgLRgyoLQOF4/Rz4Ne/5fISD59MMrKschnH5h472GYdEksrlvLImkcod5fzy3m/REqJxdi3hXmKgafmoYcIbe/fcNDWyZPI++Uv+1Rn27ZtzJw5MxHWGcBoNDJz5ky2bt3KmWeeyZYtWwiHwyxfvpyFCxdSVlbG9u3bWb9+PSeeeGK/XkNXqB7AAVTVbQZgbfUG6uPhjweKVrFJ9dazY/XHhN0mkv1BMBuYv0v3/JnuM5AWcGMecXQKgDEtDUuuk/ymZjIC6XxQunSwTTpkIpr+N1m8azE3fHgDp7566iBbpBjKHBz6+eB0q9XK1KlTWbduHStXrmTevHmccMIJLF++nOXLlx+R4R9QPYB2VLr0aJbSEGHt/t2cNXHGgJ2rdVI05ePfUuANE2jSffEdc6fgXb6F5aUVfNUwFWjCPOLoHAICsE+egHeli+8FdvNEII3SxlqKM3MH26w+4wl7EsetQ1l7WvYwJrX7zT0UR5a+vqkPFFOnTmX9+vVomoYhPn+naRobN25k8mQ91tf8+fNZtmwZHo+H9PR0jj/+eP70pz+xfv16br755iNi57DtAXxW8Rnnv3E+/ogeimhZ5TLWe8pJjekTwLsa9w3o+d0hNwDpYT8OESTiNaEJgWO+3vWz+gxYN0aJpaThPOXkAbVlILHNO5lY0Ehxi74obHv93kG26NBwh90d0j7Y88EgWKI4Ghg3bhyzZs1q59nzwAMPMHv2bMbF1+GceOKJPPnkk8yYob9oTp8+nZUrV7Jv3z6mTp16ROwctgLw77J/U+4uZ2vjVur8dfzwkx/SooWYE9Q34N3bUjWg508MAWl6rH+3x06LMxPLFH11baDJQmajm7RrrsHYhzDQQw3bDD3Mbd5LaaR7JKXNR+eiME+gmSRhxmnMTKR9WfXlIFqkGEr4/X4KCgoSP4899hhPP/00u3btYty4cRQXF7Nr1y6efvrpRJ358+dTVlbGCSecAIDJZCInJ4c5c+Ykeg0DzbAcAtKkxsrqlQBsadhCqas0kTc6EsEgYb93YAWgxd+AkBL3FxmY83wEvBb8WXmYC0cD4Ku2ApA2vcM2zEcV9hkzSP7GN/B98QWj6iQVAyysA4W7bjMpkQDJgSS8TsF3Jn2HV3e+SiAawG6yD7Z5ikFGi7/IHczzz3ftUZiTk9PBNXrp0qX9aVaPDMsewK7mXTSHmgHY3LCZJSVvMjIS5fuuFi53e0mPQmOwtl/PGdWi3LHsDlbXrAbAVbeZMzZqhPZaqN2QgvSCll+AOTcXhKC5QV/4ZT2EGEBDCWE0knfvPQBkegU1/ppBtujQ8ESDODWNW921TDRfyUmZ04jKKGuqNwy2aQrFITMsewA7S94DwBzM4qO9H4GUPPpxmG9k+UnKipEfjVJm6N/tJ7c0bOG9Pe/x3p73WH3FalzNpSzcrKu/wSQx+TRsRaMQFgumnByitbUYkpIwHQFf4IGmdRVzvht2Bo9SAYh4cWoap4brSN/xEuNLSmF0Ic+s/YSTCk8YbPMUikNiWPYA9lWtwigl5zToY+u5LijcYKG5RI96OSoaIigb+/WcrUNOAG/tfov6iI+U+FY4EZ+uw9OO0yd+zCN1rx9jZuYRCdsw0BjsdgxWA/leDXekTVjLW8oT7pVDHU80QEpM8qTpu+Q4rTilpCgMZZ7NiTJSSi5/93J+v/b3g2foMEWtMtfp630YlgJQEfWSH43y0/Bq/rm/jt+t1138Ao0W/BEz08s1NGMTLcH+26xsRdUKpmRMYXLGJF7d9Sq1WhB7qH2ZpAl6dM2sH/4AAMfChf12/sHG5LSR7dPwS321Y6mrlPPfPJ/rPriOqBYdbPN6xB0LkhQysyc4l/QFv8djXMiMkMQV253Y8Wxj/Ua2NG7h6S1P99Caoj+x2Ww0NjYOexGQUtLY2IjNZut1nWE5BLQ31MSocJTUiI/JUQNflRdjp5mI10TFsixm1wvyR2gs3bOZCybP65dzltSuZ4EnxtSwh99lpYIAWwhCjhSsXt3F0DJK3zTFceKJTFizukOc/qMZU7qDbI+bmPCwz7OP/+x4FYAN9Rt4ccsHXDn9vEG2sHs8MsKxXxmYtv5h9i3W0467IchbKYKtjVvJtGVy3/L7AHCYOwYGUwwcBQUFVFZWUl/fv8O2RyM2m42Cgt7vHjjsBEBKSUXMx3mbJbs+zafBkUqWt5mk6RPxb9qJVq8PuUzcL1lRsalfBCCmxfAISWHMw3EhP5CKMSYxR6FpZBHWnZsA2sXgN3YSXfBoxpiZibNG9wD6xWd3sK1pK5NDYfaZrLy6/b0hLQCa1PBKDUvIALR5e8xvboEsJyuqV9AUaKLSW8n07Olsqt9EOBZWoSKOEGazmTFj1IK8Q2HYDQG5Qi48SEaUJAGQ5XMz8vePM+qfL2MZ0ebjPaVCsq1xW7+c0xvUPY6StmWS59EFJjkeUywyuu9x/o9GTPmFiKD+ddvWtBVTVHLrv6NcUBFgb2DNkN443hvxIgUYI+03ybE3GjGG8vms4jMqvBWMTR3Lt8Z/C4Aa39E52a0YXgw7AWjw1YGUpDVIPFNmMvoffyflrLMQVitj3vuYgv/7X5InpnNMpaQ6WNIv53R7qkgOSI5fFsRTrb+ptAqAGKsLQOZNN/XLuYYqplET0SIGTq0YxfWeGE+vMZK108KFL5owxvy8W7LsiNnSHGxmXe06ylrKeHLjkz2OHbeGgbD5wTeyiDFv6aG6g81mijxOtjZuZUPdBgqcBYxw6HGbqn3VA3sRCkU/MOyGgHye/eQ3QVIwhvvk00maOzeRZ7DZcJ58MsH3i8ncuZpYbC/NgWbS7emHdU63rwZHQD+OSCcQICk+AWzLyWbixg0Iy9d7uCBp7nEAXLtjPzPG7eelpgXMQN/6cv4OeCHl31w0qW8B1u76/C6Szcn86vhfEYwG+bTiU47JOoZCZ2GXdcKxMAtfXohEMj59PCXNJVw47kJyk7uOT+QL6nM0Nj9oY/OxTZyAKSeTYLOf/w4v5VLy8UV85JR8Sf3KdZAPVQO8kFCh6A+GXQ/A661mRJP+xpc8ZXKnZSwTpyEQ5Lok/969lIZAw2F5GLT463DE3/i1mJ0ZwRDJQb29pIw0DFbr18Ldszvsxx6LNT8ZZ4kXKUE2g0hLw+iwcPb2CCXe5YQi4T61+W7Zu7y882UA3tvzHr9Y9gvOff1cmuNDbp3REGhAot/7kma9h7fP033cJ398OMceiCXWNNgmjifYbGZ8uG3oakxLJbOWlXH2Vxofl/RvSGKFYiAYfgIQbMIWf8440juPsWOZrodiLWw08P/W3cPJr5zM4h3vH/I53f4GHPEHvgwb+XNtPbfV6G+VKdlHdqeuwUIIQfo5Cwm1mAm1mEhzeUiadgzOk09iTLnAHPXyp6/ePKS2Y1qMHU36A1cieX9P298qHAkQjbVN3NYHOnqK7HPvI6pFuxR5v78BgyZJCkYx5+QAYDtmGmGPGe8ee+Jv6yjLwl2WzLWfaJQ2VxzStSgUR5JhJwC+QHObAGSkdFrGMkmPzvfNfUaubtEf1C+sW33I53QHmhJDQIQFqZrGOJ/u+56SfXjDS0cTju/9FyBxlSVR4KnHNnUqqd+9HhEVXLBO4/WSN3rd1oFrB6p8Vexq3sWMlGLG4OCZDa/xYfmHLN32IvNemMu8Z49ndUU5oPcAAMyGNhfbh9c8zNwX5vLY2sc6PZc/6CLVBwIwZ8d7ANNmAlC9Kp0bl+m2ZGzVe3HNKdAS7t4lcVP9pi7Pp1AcKYafAIRasMV77Y60zgXA6HRiTDZxbHMjtze5cMQkMXHom5q7Q67EpK+MC0osot96Z+bwEQBzfgH2qeNo3uXAJDVSzjqLpFmzSJo0grNXa3i0sl631RpNFfS4/CXNJUyo3MDpzfupDZVw5+d38ou1DxMVgrA5wJPrXgGgMaCv8J6VMytR3xfxEdWiLK1Y2um5/GEPafH9gazZ2QDYpkxJ5J9UEeb2hmYcjfoXy+GXBLS6bu1/f8/7PLvlWVxBV7flFIqBZPgJQNiT6AFYncldlrMUjiDk1ufInTEDQc11yOf0hFpwxocJotXVNGx1EAsZiAoDxqThFUky5+7fACDMZmyTJgHgOH4WyV5BUtjHvuaeF/OUt5Tz9Oa21bYrq1fiDrsZH45wTDgMQhLVogS0CEYpmRCKscn1CVJKGny1CAmekvaCPjWcSrm7PLFRz4H4w25SfPrfz5aj9wBMubmknHce5vxsoo0WLtsXwBTVEPkZmKMCa6SZmBbr8hpq/Xqwwb2eo3N/BMXXg2EnAN6IB0dII2w0t1t4dTBJC84g0Ggh7DWSGdPwxlyHfE53xEuGv218uX5zCs11OWgO59d+8vdgkmbPZuQTTzD6+X8m0iwTpgGQ1wyr9u/ssY2Xd77M89vbwuy+tktfmjsjFOKYUPv4GoWRKN/ytBCgij0te2lwlZGuxfhuUN+Q+5seL6f4/PygQX8Qb6jb0OF8vrAXe/ylwR7vNQohGPnIw+Td91tkTFC7Xp9PSj5eHz7M8GqUu7qOKFvriwuAWwmAYvDoUQCEEM8IIeqEEFu6yJ8khFghhAgJIW4/KC9NCLFYCLFDCLFdCHFCPD1DCPGREKIk/vuIjYP4In6cYQiZrd2WS//uFWAwUbF2DNOqI4QOsQfgDXvZHWwgLdA+XTb5SZ047pDaPNpJOfMM7DPattts3QQnr1myubbntReV3rZNZWZaJuGPBpgcCvNK5aWILUnYIm2xUIojEU4M6ONvn5R/ToO7gqxojFP8fm5qcnNfQxNP1DUwN+7rv6Gu4+I/f8SHPawLuD3F2S4v+aSTsI3Owl9npdnqIOOkbwCQ4ZFsrSvv8hpaw2IrAVAMJr3pATwHnNVNfhPwY+CRTvKeAD6QUk4CZgDb4+l3Ap9IKccDn8Q/HxG80QDJYQhbuh96MeflkXv3LwlX+5m1RSOCPjTwzJZn+NUXv+r1+X6z8jdsiDRhDnXMS5ozp0+2f10xj9GFML8JSl3lPZY/0Mf+7j2fYo2aubrezWX/+ZT6jSmcVJXD6XnXAZAVtJBRacAasbO8aiUNgXoKvDEa38/k+/u8tE4F26XEqBkobeg4BOWP+HDGewBGR/thQ2EwMOLPz5L67YuZsvhlzGP1iK4ZXvjtmp8m5hwOJKpFE5PRS8qXUOmppNpbzflvnM/NH93M1oatPd4DhaI/6FEApJTL0B/yXeXXSSlXA+3W8gshUoAFwNPxcmEppSuefQHw9/jx34EL+2p4X1i1r4xHv3gNAG9Uj8IZtfYcMS/ju9/FOjqbVA9gCOOP+Hl87eO8VfpWt0v9PWEPT6x7glpfbcIlcWQngUWT5sztmDgMMVitmFJMFDdJtnmWsKZmTZdlpZTs9+5PfB4bjnD9nimcsKvtq7ywNspY07n8stnD3C9SqViaxQmlNrY0raU67Kag1kqw2YKvVl9890F0DjvfyOc7y2JUe1wdzhmIBnDGewCGpKQO+dZx4xjx2wdJGz8WU9FEAEY3mQjGfKyqXtWhfEOggZM2Rnnsr1H2uvbw06U/5Z2ydyh3l7Oqajnf+/dVnQqHQtHfDOQcwFigHnhWCLFeCPGUEKL19SlXSlkNEP+d01UjQogbhRBrhBBrDjXa3/1fPMqzJQ9S72vEr4WwRQSxXggAgDk3m6R4/J6djW1eKt1tCP7Pbf/kqc1PccV7VwDwP3UNZPugfPxMMr//fbJ+9CMMDgf2mTMP6Xq+jlgKRnBsTRhDBO798rdoUvfd94a9NAXb3j9aQi34Ir62esBI0YDL1zY0c3JwA8d/dgWXu5qx1OrzPFMaIRjz0UCU3Ab9bx/xmvjf6DeJTrgNLSS4YEUMf7St7Vb8sSCOkCQmDD2u2DbYbJicZi6u9oEUlLW0fWde2/UaO5t2UuOrYXKFpKARCuoNbG/azis7XmRWMMQrlVVECfPHr17u+01UKPrIQAqACZgN/J+Uchbg4xCGeqSUf5VSzpFSzsmOu+D1lW+NuxJElN98+SiNMow1DJq1d9435hEjsHgFSMk7pW0LjF7d9mmn5UMhN89v+AtmzZrw9JgXCKKFBLGUNHJ+9lOybrmZcR9/1GE4YTjjOPfb0GTmjpIW9nnLeL9MF9izXj+LhS+37Yuw37e/Q92phr14fVYiFn1eJ+Izkr+qjt278zBJPe30praFWRmN+lt82GuiKpZB4Xt6aOqdowWhWMeumi8aJCk+b9SbSXvrhHHgAlskmU21uwBduO5fcT/PbHmGqrJPyHHpZedvmwBAg7eeqz+P4diYxDGeGP/e8+awj2+vGHgGUgAqgUopZWsfeDG6IADUCiHyAeK/u3eaPkzOHzeJqGsOS6vfYR9RrGGQnXTlO8NcMBoRMZDqN/Pq7n8AMCsYZE9zxwcRwPayJXiE5Hf1lUxvvoD/raljg38GhqBk6hzdd1wYjRjT0vrl2r4upF16GQa7lRM2BBgZFvzm88eo9zUn3DJbH4YlVfqCvN/X1vNyZTVSg2JRRdhrwDdyDAZnMrXG43DvTSKyxkBWi/7Vsns0jol7CVnd+kPcW2Xj1E/XYNmgt2mUENI66QFoYZIiEO7BcaAV26z5hNwmigIaK2o/5aI3L+S9sveR6BFmP9z9Jnku/XrmxHu1x5VpjFhjwbUpmZ+/HCEkq1hZtZaYFuPdsncJxTqZRFIoDpMBEwApZQ1QIYSYGE86FWh1sXgbuDp+fDXw1kDZAZD68f/wQdkKptbrG66YIoC9lz2AYn1S73vVupfIXZ8GufwDMJo7Xxi2Zf8KkgOSMf+xcX/lYmYGjLwZuxSArJnHHOaVfH0xOp1kXHcD3n027l3qJqTVcPsH/5XId4VcNAQaeHTjnykOh3H6RmJ5K509H+q9QuGXiNw8LKOKMO05YKgwpvvih90mHq9t4Pe1DVh9bTGHUv1+sh96iKTRyVijENYOctdCFwBbWBCx9G7Y0Dp5MmiCWY36or/dLaU89NWDAJS7y/ks3EyG/nViZHMTN8Uu5J6dbjQg7Uffx15vYlaZgac3vsQru17hrs/vYnHc1VWh6E964wb6IrACmCiEqBRCXC+EuFkIcXM8P08IUQn8FPhVvEzrEttbgReEEJuAmcBD8fT/AU4XQpQAp8c/DxhNy+sILIF7nitl3g4Nc6TzybzOMBfokSUvarHzZHUdMzeYKCwxIgwBXAFvh/Jbmndw6o4Y4XI7qXu8fLpuKj98548AiYVPis7J/P4N2GfMIG2tnYtWStZ51ybyqnxVvLrrVVyxIP/zSQjny34ibhOhFjNaRGANRHCOLsBcWEisqW3OwJSdTfo0C2GPidxIjJxoDKevbZgn/4Lzybr4IoTFhDUqicrOBCCKJQwxSy97AJP1nt6Z60MIKflpkx6cLjm+U1iWGwwSDA4rZleEU8veJNpopTYtj9wbf4TBChdu0Fhd/x/+uU1fL3HgxLdC0V/0xgvocillvpTSLKUskFI+LaX8i5TyL/H8mnh6ipQyLX7sjudtiI/fT5dSXiilbI6nN0opT5VSjo//7tLLqD9I/9EvKXjiYWyp8OP3oyQHJcLeWwHQN2g3TbuVibP/jAiCMSrIaoGtde2jSEop2eiv4Tg9yjFNVbkUVboS+aa8vH65nq8rBpuNopdfwjbSwcIS/c39e/HQGdvq9vB6yevMFw7khva9t5a9doyaRv7EMSTPPyGRPvKxRxnz1pskf+tmtKiBxu0OtLDAFo2Q+t0rcCxcSPZ/3aaf22LGEpVE6UQAZBRrRBDr5byRdewYMi7/Fkm7rHz2RT3XNHv4W7nGNxr1Xc8u3a+fI/XcbyI1QfauJgJVFlyjx2OwWHDOKGRieRQpw1R49LmLXc27kFLyfxv/j5d2vNSHu6pQdM2wWAlsHTcO55nnkf/gf2OO70qVntV5JNCDMaWnY8zOIlRWTmx721tYYb1kR337iI/L9n5CdSxE0T5B0JGK1uzH7Nd7CZaxY4fdqt9DxTFvBrnVcE9FMze4dAF4t3QJNb4azg903DmsZO9YQJ+wTzn77ER6yjnnYMrIwHnZLSTPP47m3clE/LpXkOO4uRQ++RdMGXo0VmGxYI6CRoCYFmvnhuknhjlCrz3HAHJ+eQ8Gp5OaLzLY/W4ex/qreKTxdzxRlcWiSr2dlAsuBKB+k95hTosvIkuavwgREVxeGeDqqihZkeNZVb2Kmz++mf/d8L88uOrBXtuhUHTHsBCAVuyLLsI6Tl90VFTYe48i2/jxhEpK8H66FOtEfUqjsAHKXG0LkqSU/PmLX3Px+iiWsIQ77yXzhuuxz5rF+M+XUfTiv/r3Yr7GOC+8AhCctiNGhqZh1gTrGnWvq+PqOw6FOBv0IRbLqFEYnU5y7riDvPvvb1fGNmUa0aABn09/+JpH5LfLFzYrpqgEIXlh01MsemURf171BjEthl9KzGHQbL2P2yTMZmxT9fmjqN9A1Xr9+3ZKaB2uahu+nJHYZ7UFpBv99tuc8qOrdFsXXQjAVZ9HOfefkou/1MNjrKpeRV6y3otUW04q+oNhJQAAjpMXARCp7TpOy8FYx48nuGULoR07SP3m+RiT9R5ApbtNAP5T+g4lIQ/nfGnCPXYSMy85i5zbb6foxX9hys7GmNq7HocCrHMXYU3TaNjqZH9lBnOq9DUBWZogzdXeG0bYbCAlCIG5oACAzGuvIf2yS9uVM2ZkghQ0t+iutwcPxxmsVkxRvYe2LB6W+sktv6O0pRRNgDUikL10HGgl87prMaan4zzrLPxVFqIRI+59Npw1foxz5yGEIOsHPyD7tttImjC+7frHT0RYLbj3JoEmOLm0nhGcyYeXfMhjC/UQ0pvqNwH6i8fLO17m8bWPo0mNQLTjEJZC0RXDTgAyrroK6/jxpJ53Xq/rWMe3/XM6TjkFW56T4nrJZvcS3GF9iOL1Tc9w8boYyf4YhT+7TQ33HAZCCFK/dwPRgBHPFzZufVv32jnT4ybQ0H4hln3WTABM+XkYulmkZczQw00FXDZiRmNiZ6/EOW02RDx4566g7kUkjV421m0EwBzu/bxRK44FC5iwYjnp370cojFKXstl/3J9yGnceacDkP3jW8m6uf1+0MJoJHn+idimTCHt5GkY6yUZ20YgtFQmZUzCYrCwsV63698bn+KBVQ/wzJZnmPGPGRz3wnE8tuYx7l9xP9saO8Y1UigOZNgJgCk7m7HvvI1tcufbQXZG0rx5mEePIu/++7GOGYN1wgRGNEqispHFO99EkxrrPXs4dT1U5BeTf8qCAbyC4UHGTbcx6rnnsE8chcljYElpFac8m0HVynREwahEudbV1JbCUV20pGNK1wXAGErDlJuHMLT/6htsNgwxgZCSZi3uJipgWeUXODWJMdp3AWgl6YChnvwHH6To1VdwLFrYTQ0o+NMfKXrlZVK/exNIweMNv2f/owt59onfUJg8idU1+tqFtRufxXTAgjGTJnh267Ms3rWYK969El+447oGhaKVYScAh4KlsJBxH36YGFawzjoJEROMajTz5b6NlLlK0QIx0psgPOcE9fbfDwizmeTj5+E84wzQBM4aI85AAPvcuYx79SXMhbp7blKrAIzqeiN4AGNcAERdPfaRIzqeL/5wN8c3GmsNK72yejnTglGEBMMh7t0gzGby7ruX/IceIu2Si7FPm9bjd0QYjQiTCfvxCzAkJxHwjsK5wsMpL75EdWU225u20xRsYrdBY0YwxMN1Dfz5Iy9/WanPh+RGo0QJs6VORRtVdI0SgEPAOlN3NTy2JsbO5p2s3/MRE/brb2G5848bTNO+dpjH6D21qhp96GTEA7/FlJ6OKTsbQ1JSYlLeMnp0t+20CgDow0UHY4gLgCXuZDQ7qAtAMBZkvFc/NvZy7UhnpH/nO6RdfFGf6wmzmeT5JxLc2EhkryTiMTF3vz7s+Mm+T9itBVi0TWP6Jxay19hI+czBn3c28pud+kLF0sbqQ7ZZ8fVHCcAhYC0uBuDYmgAt0UqWlX/ErAqNmBBMPnneIFv39aJ1stbXlIY0mxMTveYRIzDl52POy2PkE0+Q9u1vd9uOMT0jcWwdN75DvrDri7QyG8dxUdTCKb62ydS8gN4tSE53dqh3JHAsbD+k+K3qHaSbivjNit/gRWPeEgst5W3ilPVmOulvpzKpQrKvpffODorhhxKAQ8CQnEzyzIkUbzSS5Y6y1LObGfs1qjMLutxnWHFomHJyAbA1tGAbOzaxi1vOz39OwR//AOgbzPTkZWVIbntAdjb/Y0jSvYOK6qZwT0uIEdG2TedHxJcpjp5cfOgXchikXnghhX99kglrVmOwmxm1s453Nn+JI6JPegft8Z3tTCaSjj8eoeleU9ktkiqvEgBF1ygBOETy/vsRDBHBidskSElmvRH/qMF5QHydMee0rdewFo9tS8/NwTp2bGdVOuXAMXfblI4CIJL0t3tnLACBZlLjD1GA9BojGoKc42Z3qHckECYTjgULMDocOM8+l1CLmfr1OXyyv5Tf1TVgiHsvJR93HClnnZmol9MCdf6GQbFZcXSgBOAQsYwZhykJTttn5cbqAJagxDJxYs8VFX3iwPj7SfOO75c2TZmZHc8TF4C7xQuYIl7sB4ZirkumOacAo8PRL+c/HEY89N8kL1wA0QKSpOQMVwBLOIb38msp+N8/4zj55ERvaKRL4grpK5qD0SB3f3E3Za6y7ppXDDOUABwGlpxkCl0ert2jh3ZU0T4HhqQ5czAXFpL27W8dVjvp3/0uqd+6pNM8g0MXAKHpD/5Ef0FKjPUQnTjlsM7dnyTPO57I/v1EjSOI+OKhLcaPw2CzYc7NZcKqldgKksl3STwRffzqs8rPeLv0bX7y6U8G03TFEMM02AYczVgLcgiu9BBs1neWHXfCrB5qKA6FUc8+A0J08N3vK3n3/LrLPJGkvzXLWHv3zPwmMEc00ucMzvBPZ7SufQgYp4NPD5GRXtzeC8qSlUrmHi8BTXcL/aREj7he7i5nc+1upuWOO3IGK4YsqgdwGFiKx6JFDTSXJVOTXUh6TsehBcXhI8xmhGlg31UMzjQAtIMEYHyV3iMYs2DoeHfZpk5BJCXhbhyJy3wyAFkT2s+HmPOzSfFAVDYRi0b4vHIZs4NBAN7c/uURt1kxNFECcBjYjtHf+KM+I45FJw+yNYrDoXUOoCEylfh2xLxdWcVNu0IELTacEzu6jg4WBquV9Msuw/3v9/H+ZxNp3/5WYqVzK+aRBRg0Qbo/xKo9H+M1CM7x+jFrgm2N2wfJcsVQQwnAYWA/5xqs44sAOObS3scWUgw9DDZ9s5fQqmr2bDmeqvAsxkSiyDo7LaPGH/bwU3+Ted212OccS+b3byD31x2Htsxj9L2Gc1rg3ZJ3ACiKRBgdhkrf7iNqq2LoouYADgNhNFL08mv416zBPm3aYJujOAyErS3Wf2jbPkLbIOciA7GAgZTiosEzrAtM2dkUPf98l/nm8bpDQo4LljbqcYPcVaOYaXfxmnUvUkoVskShegCHiyEpCccCFfztaEccsN2jY9EiACI+I+ZwlLyCnEGy6tAxj58JwKhGIx4tyOh6jYIlPk7/WCJFkAp35eAaqBgSKAFQKACDXe8BZN50E1k/+hEA++U0TFLDmpHeXdUhicGehCkJiuOrmCdW6pPZ6SUWnH7Jiv2bB9E6xVBBCYBCgT6cN2n7NrJv+wnmeLA4Z+E5ABhSjs7wHuZ0K+Nd+jLhKQfsXjquCjbUbh0kqxRDCSUACkUcIQRCCIwZGQiLhdCOHQBH7W5u5uwUbJ4o/10bY/ZeQVOhHqpkVJOJXc07Btk6xVBACYBCcRBCCEz5eQR36nvxGlPTBtegQ8Q2dTqaX/CNrU3YvBq2c78JBklRM1T6SohpscE2UTHIKAFQKDrBnJdPrFGPo2NMPTqHgJxX/QyA6lXpeO0OZt74PcxOE+NcMfxaM/csv4fylvLBNVIxqCgBUCg6wZyfnzg+WoeALKPHYC7Qdz/Lu/NOjElJmDOSyXdHsMpc3i59m/tW3De4RioGFbUOQKHoBMsBoaaNR+kkMMCop59B8/mwTdGD2ZlzMgjVNONouo4x495gQ90G/BE/SeZD3+1McfSiegAKRSe0PjABxGFsBTnYWEaPbnct5lFjiAUMPN74CDbv+cRkjHV16wbRQsVg0qMACCGeEULUCSG2dJE/SQixQggREkLcflBeuRBisxBigxBizQHpM4UQK1vThRBqI13FkOLATWO+TitmzdNPAQRTwnvJ2FuLSZj4qOzzwTZLMUj0pgfwHHBWN/lNwI+BR7rIP1lKOVNKOeeAtN8B90spZwL3xD8rFEMGU0ZGz4WOQoyZ+nVpIcEToQc41u/ljR2fDrJVisGiRwGQUi5Df8h3lV8npVwNRPpwXgm0DqymAlV9qKtQHBGS5s5NxN7/umCMRw2NBfV//eMDQaSlmoaA2jpyODLQcwASWCKEWCuEuPGA9NuAh4UQFeg9h7u6akAIcWN8mGhNfX39wFqrUBzA6H/+g6KXXhxsM/qV1u0woyH9X/+EgL5HwFfVXw2aTYrBY6AF4EQp5WzgbOCHQojWqGm3AP8lpSwE/gt4uqsGpJR/lVLOkVLOyc7O7qqYQqHoBcb40FYsLgATwmGQBnY07RxMsxSDxIAKgJSyKv67DngDaJ3svRp4PX786gHpCoViADEkJyPM5sQQkBmwhZPZWl8yuIYpBoUBEwAhRLIQwtl6DJwBtHoSVQEL48enAOrbp1AcAVpjHUVDxkRaVtjCnpayQbRKMVj0uBBMCPEisAjIEkJUAveivzggpfyLECIPWIM+qasJIW4DpgBZwBtxFzoT8C8p5QfxZr8PPCGEMAFB4MD5AYVCMYAYMzOItrSFBx0ZFnwVqiYUC2E1Wrupqfi60aMASCkv7yG/BijoJMsNzOiizhfAsb0xUKFQ9C+m9Axi9RYAashidERjFRp73XuZkD5hkK1THEnUSmCFYphhzMwgFjLgiiXTvNPJzHrdE6jMpYaBhhsqFpBCMcywFBTidmvUfJQKrhDjXGGYZqK0pXSwTVMcYVQPQKEYZmRefx0Zl5xBLG0kADYimLVsSl1KAIYbqgegUAwzDMnJ5D74BLlA2WnzMYZqEJEcNQQ0DFE9AIViGGNKcaCFBMZACqUtpTzw5eODbZLiCKIEQKEYxhjTUomFDdziXwvAy7ufGWSLFEcSJQAKxTDGkJZOLCS4NlTCj5pdAIRj4cE1SnHEUAKgUAxjjJnZxCIGpASrJgHwhAODbNXwQ0rJe2Xv0RJqOaLnVQKgUAxjTLmFIAVaRGCVugB4Q8FBtmr48e89/+aOz+/g71v/fkTPqwRAoRjGGLLyAD06qC0hAKoHcKR5atNTAPgiviN6XiUACsUwxpiWBkAsbGjrAUSUABwKn+z9hAdWPoAmtT7V84a9iUV4tf7agTCtS9Q6AIViGGOKC4Av6QSscrV+rOYA+own7OG+FffhCrmYnDGZSyZc0uu6FZ62wHxV3iO7OaLqASgUw5jWHkD9W7tJatAfB76wmgPoK2+Xvo0r5GKkYyQv7HiBcCzMW7vfwh/x91i3VQCmZ02n2lc90Ka2QwmAQjGMMY8ahePUUwGwtcQFQA0B9Zmvqr+i0J7D3Fg2pa4yrnv72/zqy1/x963/7LFuqwDMzZuLK+TqlWj0F0oAFIphjDAYyH/gtwCY/QIAXyQ0mCYddWhSY13Nao6tK+OEvR+jyRgb3XpYjbd2fdxj/QpPBemmZAJVes+rxlczoPYeiBIAhWKYY0xNBaMRU0B/HARUD6BPlLlKcUU8HBsMMSEcSaTPd5vYH9hJY6Cx2/oVjdsZ5W3irC2PArCp9sgF5VMCoFAMc4TBgCkzA2NA7wEEomoOoC/sLdPf8puDxYyOtAnAFZ4GQLK1cWu39euay8iLRimKRAH4vHzHgNl6MEoAFAoFpswMRKIHoASgL/h9uuvmJ5HjMQPz3GZubXIxNeoFoLxlb7f1XbEgrlg2mqWApJg4olFZlRuoQqHAmJVNtCYuAFE1B9AXAmH9QV8bziWsmfljQwV2EUYCxpiJzbVlMLXzuprUcAsJERseZz5Fkd3sC+w7YrarHoBCocCUnYMM6o+DYEz1APpCIL569/ZP36X0rWxshAlKMzFpIC1ipqR5T5d1PYFmNCG45pVmgpthYsSPTztyawGUACgUCkzZ2cSCBoSUhFQPoE/4o37yGyWjXPpQUKjFRI3MoMoymtHRGDX+/V3WdbfswxyRZLZEkCv3MN4bRhq97Gs5MiuClQAoFApMmZkgBak+QSimBKAv+CMBjtvdFv4h0GihyFDLbsNYpsY8+GJ1RGKRTuu63BWktrr9B8PM2wRCCh796o9HwHIlAAqFAn1jGIDUgCCkhoD6RCAWxBnXTENKCoEGKy/7F5C1tJEF+7wgNB5b2/lOay2+alJb47/ZkxDbk5janM7SqneJarpXUDAapKyljEC0/91zlQAoFAoMDicAjhCENdUD6Av+WBBnSBIyW0maPZsAkzl19vcw761jxBobM91J/Gv7i0S0jr0Al6+GVJ8ehC/1yiuJBows2OtDI4Yr5AJgZ/NOLnjzAtbUrOl325UAKBQKjE4HAClBtSNYX/HHwiSFIGyxYZ81i/CectwvvwyAr8bK96r2oxFlj6u9O+iKqhXcv+fNxBBQ2skLARjfoncJGgINgB4tFMBpcfa77UoAFAoFBocuAI4gRFQPoE8EtDD2sCBisWGfOROA0PbtpF95JQa7lcINZgBW79/BPV/ewxslb+ANe7nxoxsJymhiCMg2aRLCbCS3RR/qqffXA3qkURgYAVDrABQKBQan/nBxhiQRTfUA+oJfi2ILQ9Rmxz7tmER61k03IrQwTf96CYdf8mH5EtY3fcobu9/gg/IPEuVSfZKg2YbBbsecm4nRoytCpVv3BPJ49AihjoAb0vrX9h57AEKIZ4QQdUKILV3kTxJCrBBChIQQtx+UVy6E2CyE2CCEWHNQ3q1CiJ1CiK1CiN8d3mUoFIrDwdjaAwh9/XsA/oif7y/5fr+NqQekLgAxqx1DUhKpF11E9m23YcrKwnHGOSAF0ysE65s+BcBkMLG8ajkzQjEAUv3gT04BwDJqFMJjBGBXo/7g98RXEjvd/R8qujdDQM8BZ3WT3wT8GHiki/yTpZQzpZRzWhOEECcDFwDTpZRTu6mrUCiOAK1DQMkhSVSGOHPxmby046VBtmpgeKv0LVZWr+QP6//QL+35iWENg2ZPAmDEfz9E1s03AWCbqi8Bnl2lT/SOSSniRzILgAs9Ln5V72JciyDq1L2wzGMnEPMasUQFe116VFBPuAWTlNjtmf1i74H0KABSymXoD/mu8uuklKuBzh1dO+cW4H+klKHWNvpQV6FQ9DPCZEKYBckhSYtWTpWvigdXPTjYZnWLP+JPjI/3logW4YXNzwDQGOjysdY3O6SGJQwyLgAHYnQkY8lNZmFFiJTwKdyWfQJX7FnNLxuaON/r4zKvmxSPGVOWLgqWUUVoUQMFXkGNNz4HEHLj0DSE1dEv9h7IQM8BSGCJEEICT0op/xpPnwCcJIR4EAgCt8dFpANCiBuBGwFGjRo1wOYqFMMXo9VIRjCGRB+aGJ0yepAt6kgwGuS5rc/hCrn4ZN8nhGNhPrvss17VjcQi/Hn9H9nrr2F6IMom9lLhqSAUDTEufdwh2xQQYAmD157cab59bD6x9W5MdWdySvpikJLLPbpnj5Rg9kUxjtafbZaxYwGYWh/hndRV1Pvr8US8ODUNLJ23fzgMtBfQiVLK2cDZwA+FEAvi6SYgHTge+DnwihBCdNaAlPKvUso5Uso52dnZA2yuQjF8MdhMjDpgMyqzwTx4xnTBR+Uf8ucNf+aF7S9Q46uhKdjUY7z9Vh7/7A6e3vosZ3h9/LxZd7H80Se3ctHbF7GhbsMh2SOlJIDEEpaI5I49AABL4UhiQSOneD8guu3ddnmxkAFzLEb2hDEA2CZOAGBKbRiExv0r7scT8eHQJBxtbqBSyqr47zrgDeC4eFYl8LrU+QrQgKyBtEWhUHSPwWYiKaSRqen+6K1+6EOJL3YsJiMW4zSXMZG2urbTwYMObCx5l9nBIA/XNzIqHnu/rEXffOW3K397SPYEY0GEBHMMDMmdv6GbRhQAcFf4eUr9mfw45zlcJ93HroJLCHgtAKSM0XsAxqwsjE47i/aHMYZy2e3ajTcaIOVo6wEIIZKFEM7WY+AMoNWT6E3glHjeBMACDL1vm0IxjDDazRCR/LgxwqLIMbhCriG1KCwYDbK8eRsn+oM83ryHNeX7MGgmXtn+ViJsAsCelj2sr1vfoX6F2cSYcBTPXjsNb2Yz64CNt3Y176LaW92und7gD/uwxW9RVwJgLigCIOI3EnlbcPX7z2NOOp6kNSYq/xMf+y8sBEAIgbVoBBGXGbunkCpvFfVRHw4pwWTtk229oTduoC8CK4CJQohKIcT1QoibhRA3x/PzhBCVwE+BX8XLpAC5wBdCiI3AV8C/pZStzq/PAGPjrqUvAVdLKWW/X51Coeg1BrsFQyTGxd6XOMWlj6vXB+oHxZaV1SvbhU6IaTGufP9KXFqYs3w+tBgIt5GzGk2srvuCR9fo2ym6gi6u//B6rvvgOpZVLqP1seINumk2GikMR6halU7Mb2R2uZ43OaQ/we//4lHmvjCXd0rfaWfL6j1LuPm1S1j0r9NYVbWG1TVtPQ5/sBl7XABMji56AKP0YR1/vQWjJkkq2ca+a6/Ds/Rz0PQgcuaRIxPlrcVjCLWYSA9ZkEgqYz6cGKHzUfLDosdJYCnl5T3k1wAFnWS5gRld1AkD3+uNgQqF4shgsBrRIvo7YWpUf9jU++sZ6RjZXbV+p8xVxveXfJ9Lxl/CffPvA2BD3Xp2NO3g1w1NzKuNUPZZDhGfiRtTmqk/bxQv8C/OKz6PDzf/g6ZAAymmTH74yQ+5bdbPuX76VVTEx/jL6mcwX9N33Mr3SECwwB+g3Gzmy9oPAVi8azHnF58PwNrqr7jxs5+Somk0GY3c8NG1ANw2+zaun3Y9te59iR6AydG5l45pzCRADwsBYL/metImjcOxcCElJ8wHwGC3J8qb80YiYwYKAoKKeJpTDMx8jAoFoVAoADCmZhALC7bHCsiPrwYejB5AY1Cf1D3wTfzjbS9i0SQn74iyctMkIiEza8/8DtGQjV8v20NKVHD9v3/AG3s/5Hi/nw92r6corPHMer2NitqNAJjr0/QGDYIcr+7tVLjTzhMf+ri1ycUEdzrr6tZx3hvnUeev45Hl95MXjfJOZRWne9oWyD2x9g/U+Gooay7BHk+2ODsXAKMzBYNJI9CgC0DBD28i7cILMaWnk/vrX5H1g1valTdk5wHw3cC6RJpzgCbklQAoFAoAzHPPRcYMFC78ESOi+vBLSdPufmt/acVSrnjvCmJarNtyrQIQ1sIEo0FCsRAfVC7lvIowDZ9nkFPZTOp5F/C9J+7FecbZRNyp/KmuFp9sIhSKclptELNf8A23jxatjJgWY32d/jBNaTSA0UjylJGkePXhl5RNTtI22rhmv49ffVJBYb1kr3svr+x8ha3efXx7X4RNH03jmvcjpAVi/LGmHonk+W0vUta4ndSQ3o4zPaXLazIl6ddcZ0/D5Gzz5sm44gqyf/zjdmWNWfkAHB8tZWZQV5c0o623t7lPqFhACoUCAEvxeACEz0KqJrEHMlha8QU/mHVLDzV7x08+/Qma1PBGvKRaU7ssd6Bb59LKpbQEW2iQYWbtTAV0//m0yy4FwDp1Ki3vvEvmqmJe2tWAQROAk904OT03ygvXhvj9mv/l+YY1XFLrZ3JDPZYxRVhGZmDftY/Jngg5jfrDufTdXGzAfaEIN1+az5ObnkRokpnv2jGKEOZ6G089b8IYcJJ1VTZLyj+iKBZmZk0MMFA0bXyX12RO0gi7oSIlr8f7ZExLB3QX0Weqa3nWVswF+Rk91jsUVA9AoVAAYB1XDECoQX/rLPCnsqN5Cy2hln5pX5P6m3JPG5s0BhoRCEY6RvLCthd4q/RNJociZO43EMwrYOL6dSTNmgWAbcoUALw7GkktClM7PY2NF99A8vFzsdeaWLBZ8tz2vzK/KsyF/0pmdOM+0i66GNPIMYiwgcfWhjDQ5n9icCSRWgmXNDQDcOxeDbs/hv0Xd2GfOROtIULEZ+K4Kkm1v4KNwVomlJtwZY3Akp/f5TVl/+45rN/7Dqc9el+P98mYqvckYmEDZmBRMEqSpevexeGgegAKhQIAU24uhuRkah/+I/WmPC6a5eJ3p2lsqNvAwsKF/XaengSgKdhEpj2T7+SdxKO79XhEN/r8pDSYiJ6ysN2EqW3y5MTxyH+XUhD3lJGaRvmZ87hpiQfNJLlyiwEpTYx581XsEyfievNN4BUaxRlYTMuxz5iB5vOR/ZMfU3nLD/j+ykZOnhMh6asUQqZkpn/zLFwhL4ENGwA4ttrHe1MgHJMU7Jd4T5nb7TXZj1vA2OMWdFumFWOq3jvyVtmwOKLkpjeApf/DQIDqASgUijhCCLSgvh2kFjUwo1qPlVPaUtpdtV5xoJe3P+rvpqTeA8gUFi78pC1G5HHuEJZoDNvYMe3KGp1Ocu64g6JXX+XAYALCYCD/iecwRQW3viVJKwXLvPnYJ04EwJybC4Bt0zosRaMZ/Y+/M+bVV3AsWEDKWafRuNVJbMPpWMtMpF76bQx2O2mXXcqIh3+H0W7guAY9UNvIRjBHJUnHzj68G3TgNcUFoGVPErXrU0nFR9TU+Srjw0UJgEKhSJBz++2knHsujukFJLeEEDEHpa6yw263dWIXIBDpYQgo2EhmLEaapmGL6t4vk1vioZMLOg6zZF57Tbs4/K3Ypkxl/OefJz6POLXtDdwyVh/u0rxerOPGI4xGhNmMMBrJ/92jGLOyyNq4luQFJ1F0950AGKxWUs8/H9uYPAJlSXx3dYQz6nXBTB/Tf3HKhN2e8PkPteiDND4GZhJYCYBCoUiQee01jHz0EaxTZhD2Gknz2djeUHJIbf1969/557Z/AlDpqUyk92YOICOs9xLe2V/O36tqMQb0B2JaJwLQHaasLHLv+TUAjm+cmEg35+ZgyskBwDqufSA4g8VCxtVXYUhOJu+eexFGY7v8tJt1Qbh0VYwra/TNW7KKOlsKdWgIIfQocUAsZCQaEri1/l8FDEoAFApFJ1inHw9SMLVBss9TzqEs1H+t5DVe2/UaANW+ts1MuhMAKSVNgXoyXfsByNNizA6FiAb0h7A5p+8BITO++10mrFnTbrUtgDFTj69vLR7boU7m9dcz7rPPsBR0XASXcsbpZJ47h7DXSNSv25WUl9Nnu3pL2G3muTUNbKty93vbSgAUCkUHLBP0ydVJ9RFCmp/drr6tB5BSUuWtosJTgSa1dq6d3QmAJ9BIUIuQHY0RihoJNOlDQNGg/qgyHWJEYGMnYRpSztL3ubIUF3fIEwZDp3VasRSPBynwNNjw2p0Ii+WQ7OoNFd4RuHJPJBDpfv3EoaAEQKFQdMBSqA9pTGuOYhZJPLz64T7Vbww2EoqFCGth6vx17SKLdicA9Y27AHBHc3in4XrKP8oh7DESDRgJGs2Jncv6g8wbv8/Yf7+LbcKEPte1TNSj3ITqzPid6f1m08EIu520SZfz6I+v4NjR/X8eJQAKhaIDhpQUEJATClJgPI0V1Sv6FBl0v3d/4nivey+NtRtxxvR1AJ6wPm4eioX45ee/5NE1j1Lv10NO1Lp0j6Mvg8cztWwLSIl39M+oTzsJW042XWwbckgIIbB28vbfGyxT45HtJUTS+3+rxsK/PkneffdhGVNEcOdO/OvWIcP9H5lVCYBCoeiAEAJjshl7KEQ0pL959mV/gP2eNgHY59lHQ8MOCqJ6qGVXQBeAXVWreafsHZ7b+hwXvqVvyrK1QY8Y72iwwr5yANyrtuMISex5uf1xaf2CMTcPg0UXI9shzEv0hGPBAtK/cxnWscX4V65k73evwPNZ73Y+6wtKABQKRaeYnHbMoTA+n77wqs7fu627N9dv5o7P79DbECbKmstp1EJkxWIYNCPukC4A9XWbAZhbPQl/xM+V71/JH/a9B0Bas/5wTb3oIgJr1xLYsAHTEBIAIQTp194AwMQZXYeAOFwOnKBOntv9YrNDQa0EVigUnWJMdaI11vOk516+nZKfGKbpiX+u+2PiOC0i+XxPKQEZZWIshlEz4om7eDa49WDH0wKSgvw7eKPqAQBMUpIW3wog9+67cZy8iHD5XlLOOaf/Lq4fyPmvn+I8+RSs4wdOAFrXKwAY09L6vX3VA1AoFJ1iTEsjFjKQFdW9Tyo9tb2qt6nyC8aFw/xlv5u0aBRXyEWT0MiKxTBJA95WAfDVIqRkktZIRlMKD53wBwCiQpAdDWJwOjE6kkk54wyybvx+py6Zg4195swudwLrDyxjivTfYzu6qvYHSgAUCkWnGLPyiIUMZGgaSEFFS/cC0BRs4rRXT2O/ycglHh8nhl1kalH8Wg1RIciMaVg0gS+iC0B9sIF0TeNs4zpu2/4dfvlc22KxnGAL5iE05DNYWIuLybjuOgr+/KcBaV8NASkUik4xjZpALPIfhAbWmIVqX/cCsLFuI7V+vcxxAT1EQnYsQsSgrwHIjMWwSvDHQ0E0hFvIjrb5thdID0UkMbo5RIbfhWnsiIG4rKMKYTSS+4ufD1j7qgegUCg6xZiWDpqk4rNMUoPGHucA9nn2AfDPqhomRPRB/IwDNlnPjcawaRCMrwNoiPrIih0gAKKex5oinP6hgZyqsiE16ft1RQmAQqHoFGO67v7pq7Uyvk7SFOreDbTcXU6a2cHMUJu/enrc9x9gRDSKXUpCMb13UK+F2wnAE+Y/w559JO3RBcKcM3DhFRQ6SgAUCkWnGJLa4u4XujVc4bouYwI9tOohFu9azChj+wnRtPj2j8aYRCtLJlmLEdKCengIYsS86Wz+agJl72dj00JsqixK1BXWgYmAqWhDCYBCoeiU5OOPx3nmmQCMcUeJSD9NwaZ2ZaSURGIRXtzxIgB5vma2a0XURfStD1t7ABeukLSscDC9LEJEC+AJuRFROPfNKKYyL6EWM2GPCW2/IDxhCvkPPkj6Fd89glc7PFECoFAoOsWQnMzIxx8Dg2CkRx/Tr/BUJPL/uP6PnP362exx70mkpfoaKfsqi8bXDGgxSIsLgCOo9xxGNmuE8dDoqaCgETJdETxnXQBA865k0lq8ZH77EtIuuRhjP8b9UXSOEgCFQtElwmDAnGolKy4ArRO9O5t28tdNf2W/dz8f7f0IgOtcLYyun8LY8ioAAn4r6fEhIG98NCfTH0MSpaxhG0lxUWDefABcZck02FIYcdm3jtTlDXuUACgUim4xZaaQ5I2BFOxq1N/2v6r5KpH/5u43AbiuxcOzhqsT6WW2k7BrejhnixYP7eDXBWF74zaS9L3nScrPwxAPvew891wMAxhaWdEeJQAKhaJbzMXTiAVMZEYFn5ZtA/QdvhxmB/nJ+dT4akjDQL0sZMqowkS9pI0hzBUj+Zbbw+wmfU9bh0cfEtrhKkkIgCMjDc2rxweacOHZR/DKFEoAFApFt5jHjCPiM3D2pgiNAX0tQKW3kgJnAfPz9LDIueEwX0QmstDiTdQL7y6lfpmfexubyQjqD36jV3/k7HDvJVn3BsWZlY7zjDMAsM+adaQuS0EvBEAI8YwQok4IsaWL/ElCiBVCiJAQ4vaD8sqFEJuFEBuEEGs6qXu7EEIKIbIO/RIUCsVAknH11VjznSz4Sp/ABX0yuCA5n59/9jR31rdwV0Mje2UuRXs2d6gfPOZqPDY9lo3mM2KIQV3ETVp8DsCZmcqIh3/H+BXLESYVnOBI0psewHPAWd3kNwE/Bh7pIv9kKeVMKeWcAxOFEIXA6cC+XtigUCgGCVN6OvaiLKxhiOFFkxr7Pfsp8DSQHPFzhbeFY0Mh9scySfnwLZLnz29XX8y4lfHZ8d2spCDTo29wnh7UCJosWKwWDFYrpvSB21lL0Tk9CoCUchn6Q76r/Dop5Wog0sdzPw78Auj7btMKheKIImx2TFHQhI9aXy1hLUyhv/0m5cZGDRrqSbvssnbpodKyxBg/QK5P30g9NSgJWOwoBo+BngOQwBIhxFohxI2tiUKIbwL7pZQbe2pACHGjEGKNEGJNfX3v4pErFIr+xWC3Y4wCQrKiegUAo9311Mq2t/b0kD7Ob5s6laJXXyX/QT2+f6isFM3rTWycPqNZH+aJRgwErElH8CoUBzPQAnCilHI2cDbwQyHEAiFEEnA3cE9vGpBS/lVKOUdKOSc7u/+3XlMoFD1jSErGoAmMMcm/tv+LNGsas+rKWbNnHHVbnDRLB6MjXoTVinlEPvZpx5B2ySWY8vMJl5ejeb2YR+jRPRe59VhB+X5JxKYEYDAZUAGQUlbFf9cBbwDHAcXAGGCjEKIcKADWCSHyBtIWhUJx6Igk3U/fEoGdzTs5Pe94TOEgY7/aT+MWJ5XRTEZ567CMGYMwtD1WLCNHEqmqIubzJQQgL+Lh8boiCv0QsavVvoPJgAmAECJZCOFsPQbOALZIKTdLKXOklEVSyiKgEpgtpawZKFsUCsXhYUjSH9TWeHTnsXUhPPvaxu/rkk+lwFOHdeyYdvXMI0cS2V+F5vViGpEPQHLQS0rIhxY2oCWpHsBg0qPPlRDiRWARkCWEqATuBcwAUsq/xN/c1wApgCaEuA2YAmQBbwghWs/zLynlBwNwDQqFYoAxJDsBsIb1yJ4nv/Ea1VVpaMKAQWqM+If+r20purBdPfPIEUSrq/XjeA+AsCQnUoUvYkAmqR7AYNKjAEgpL+8hvwZ9GOdg3MCMXrRf1FMZhUIxuAhHCqD3AGaWSdzr9c9J3/wmwbffBCDtsstIvfjidvXMI9v28TWlpyNsFrSIgdFUsz08AuFwHpkLUHSKWnWhUCh6xOBIBcAagXn1EUB35cw46UQ46URAknr++R3qHSgABocDo9NBLOxCCwuEBEN62hGwXtEVSgAUCkWPGBxpAPylso7m/elogG3aNBwLTsKYmtplvQMFwDphAsbUNGKB/YQ8+qMne8qEgTRb0QNKABQKRY+IFN3f3x6B/R4bgcJC5r/6So/1zHl5WMePJ/XCC7FNnIgxLQOtxUDYrT96xh07dUDtVnSPEgCFQtEjBqcuADImkB4wzBzdq3rCbGbsO2+3tZOaSiSsC0DEYCRzXNFAmKvoJUoAFApFjxji6wCiIQN2fxjrhOJDaseYlkogaCDkNlOXkqOCvw0yKhy0QqHoEWHXff5bh25yJ4zprniXJM2aRSxkxFtlo/jYKf1mn+LQUAKgUCh6xBAXgKBHj+djjy/q6iuOU05JHGeee87hG6Y4LFT/S6FQ9Iiw6iGc/R4rAokpN/eQ2jFlZJA0dy6R6mqcZ3UXZV5xJFACoFAoekQYDAiLGXx61HfzIQoAQOHTT4GU7WIGKQYH9RdQKBS9wpCsh20wpKRgOIwYPgaLvgGMYvBRAqBQKHqFsNsAMOfmDLIliv5CCYBCoegVBps+EWzKOfThH8XQQgmAQqHoFcYUPQCcKUf1AL4uqElghULRK/L/+yFcr7xKyllnDrYpin5CCYBCoegV1jFjyL3jF4NthqIfUUNACoVCMUxRAqBQKBTDFCUACoVCMUxRAqBQKBTDFCUACoVCMUxRAqBQKBTDFCUACoVCMUxRAqBQKBTDFCGlHGwbeo0Qoh7Ye4jVs4CGfjRnIFG2DgzK1oFB2Tow9Keto6WU2QcnHlUCcDgIIdZIKecMth29Qdk6MChbBwZl68BwJGxVQ0AKhUIxTFECoFAoFMOU4SQAfx1sA/qAsnVgULYODMrWgWHAbR02cwAKhUKhaM9w6gEoFAqF4gCUACgUCsUwZVgIgBDiLCHETiHEbiHEnYNtz8EIIcqFEJuFEBuEEGviaRlCiI+EECXx3+mDZNszQog6IcSWA9K6tE0IcVf8Pu8UQhzRraO6sPU+IcT++L3dIIQ4Z7BtFUIUCiE+FUJsF0JsFUL8JJ4+5O5rN7YOxftqE0J8JYTYGLf1/nj6ULyvXdl6ZO+rlPJr/QMYgVJgLGABNgJTBtuug2wsB7IOSvsdcGf8+E7g/w2SbQuA2cCWnmwDpsTvrxUYE7/vxkG29T7g9k7KDpqtQD4wO37sBHbF7Rly97UbW4fifRWAI35sBlYBxw/R+9qVrUf0vg6HHsBxwG4pZZmUMgy8BFwwyDb1hguAv8eP/w5cOBhGSCmXAU0HJXdl2wXAS1LKkJRyD7Ab/f4fEbqwtSsGzVYpZbWUcl382ANsB0YyBO9rN7Z2xWDaKqWU3vhHc/xHMjTva1e2dsWA2DocBGAkUHHA50q6/wIPBhJYIoRYK4S4MZ6WK6WsBv2fEMgZNOs60pVtQ/Ve/0gIsSk+RNTa/R8StgohioBZ6G+AQ/q+HmQrDMH7KoQwCiE2AHXAR1LKIXtfu7AVjuB9HQ4CIDpJG2q+rydKKWcDZwM/FEIsGGyDDpGheK//DygGZgLVwKPx9EG3VQjhAF4DbpNSursr2knaYNs6JO+rlDImpZwJFADHCSGO6ab4ULT1iN7X4SAAlUDhAZ8LgKpBsqVTpJRV8d91wBvoXbtaIUQ+QPx33eBZ2IGubBty91pKWRv/R9OAv9HWbR5UW4UQZvQH6gtSytfjyUPyvnZm61C9r61IKV3AUuAshuh9beVAW4/0fR0OArAaGC+EGCOEsADfAd4eZJsSCCGShRDO1mPgDGALuo1Xx4tdDbw1OBZ2Sle2vQ18RwhhFUKMAcYDXw2CfQla//HjXIR+b2EQbRVCCOBpYLuU8rEDsobcfe3K1iF6X7OFEGnxYztwGrCDoXlfO7X1iN/XIzHjPdg/wDno3gulwN2Dbc9Bto1Fn93fCGxttQ/IBD4BSuK/MwbJvhfRu6IR9LeQ67uzDbg7fp93AmcPAVv/CWwGNsX/ifIH21bgG+jd903AhvjPOUPxvnZj61C8r9OB9XGbtgD3xNOH4n3tytYjel9VKAiFQqEYpgyHISCFQqFQdIISAIVCoRimKAFQKBSKYYoSAIVCoRimKAFQKBSKYYoSAIVCoRimKAFQKBSKYcr/B5X4RRlmp50HAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "del candle_df[\"TIME-UTC\"]\n",
    "candle_df.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1bf5fd6c",
   "metadata": {},
   "source": [
    "## Technical analysis library - ta.trend.SMAIndicator\n",
    "**pip install ta**\n",
    "\n",
    "Using the *ta* library we are going to load the RSI information of the current dataframe using the *close column*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a6b946a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ta.trend import SMAIndicator\n",
    "sma_object =SMAIndicator(candle_df[\"CLOSE\"], window=9, fillna=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1371837",
   "metadata": {},
   "source": [
    "Computing the EMA value.\n",
    "\n",
    "### SMA values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "96b14e45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "350    1.156260\n",
       "351    1.156232\n",
       "352    1.156126\n",
       "353    1.155951\n",
       "354    1.155876\n",
       "Name: sma_9, dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sma = sma_object.sma_indicator()\n",
    "sma.tail(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0920ec80",
   "metadata": {},
   "source": [
    "# SMA PLOT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "98396333",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sma.plot(figsize=(20, 10))"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "b3ba2566441a7c06988d0923437866b63cedc61552a5af99d1f4fb67d367b25f"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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